The reprercntation of physics problems in relation to the organization of physics ' knowledge is investigated in experts and novices. Four experiments exainine lo: the existence of problem categories as o basis for reprelentatioh; (b) differeke in the categories used by experts and novices; (c) differences in the knowledge associated with the categories; and (d) features in the problems that contribute to problem categorization and representation. Results from sorting tasks and protocols reveal that experts and novices begin their problem representations with specifiobly different problem categories, and completion of the representations depends on the krrcmfedge associated with the categories. For, the experts initially abstract physics principles to approach and solve a problem representation, whereas novices base their representation and approaches on the problem's literal features. CATEGORIZATION AND REPRESENTATION OF PHYSICS PROBLEMS BY EXPERTS AND NOVICESThis paper presents studies designed to examine differences in the ways expert and novice problem solvers represent physics problems and to investigate implications of these differences for problem solution. Aproblem representation is a

Theory raises questions about how illness scripts develop and are refined with clinical experience. It also provides a framework to assist their acquisition.

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Coactive Design is a new approach to address the increasingly sophisticated roles that people and robots play as the use of robots expands into new, complex domains. The approach is motivated by the desire for robots to perform less like teleoperated tools or independent automatons and more like interdependent teammates. In this article, we describe what it means to be interdependent, why this is important, and the design implications that follow from this perspective. We argue for a human-robot system model that supports interdependence through careful attention to requirements for observability, predictability, and directability. We present a Coactive Design method and show how it can be a useful approach for developers trying to understand how to translate high-level teamwork concepts into reusable control algorithms, interface elements, and behaviors that enable robots to fulfill their envisioned role as teammates. As an example of the coactive design approach, we present our results from the DARPA Virtual Robotics Challenge, a competition designed to spur development of advanced robots that can assist humans in recovering from natural and man-made disasters. Twenty-six teams from eight countries competed in three different tasks providing an excellent evaluation of the relative effectiveness of different approaches to human-machine system design.

A pervasive tendency for analogies to contribute to the development of entrenched misconceptions is identified. The misconceptions have the form of reducing complex new knowledge to the core of a source analogy. A taxonomy of ways that analogies induce conceptual error is presented, with examples of common biomedical misconceptions corresponding to each. In order to combat the tendency toward oversimplification associated with the use of a single analogy, an alternative approach involving integrated sets of multiple analogies is offered. In the multiple analogy approach, additional analogies are introduced that correctly convey information that is incorrectly represented (or not represented at all) in an earlier analogy. Thus, the pedagogical strengths of analogies are retained while their weaknesses are mitigated. The multiple analogy approach is illustrated by the example of force production by muscle fibers. The use of multiple analogy sets is made more tractable by the employment of composite images, with situation-dependent selective instantiation of aspects of the composite. Finally, the situation of analogy is argued to be one instance of a more general pattern of oversimplification-based misconception development attributable to the use of single knowledge sources when compilation of multiple sources would be more appropriate. MULTIPLE ANALOGIES FOR COMPLEX CONCEPTS; ANTIDOTES FOR ANALOGY-INDUCED MISCONCEPTION IN ADVANCED KNOWLEDGE ACQUISITIONFew would disagree that analogy is an important tool in the acquisition of new knowledge. Indeed, work in cognitive science and educational psychology in the last dozen years provides ample evidence of the usefulness of analogy in learning and has substantially advanced our understanding of the psychological mechanisms responsible for that utility (e.g., Burstein, 1983;Carbonell, 1983; Collins & Gentner, in press;Gentner, 1983;Gentner & Gentner, 1983;Gick & Holyoak, 1980;Rumelhart & Norman, 1981;Vosniadou & Ortony, 1983). Yet, as this paper will demonstrate, the use of analogies in learning is far from straightforward and surprisingly often results in deeply held erroneous knowledge.Our intention is to offer a more temporized and cautionary alternative to the general enthusiasm for learning by analogy, especially in its most common form: The use of a single mapping between a source and a target concept (the "topic")--what we will refer to as a "single analogy." (For exceptions that address more complex uses of analogy, see Burstein, 1983; Collins & Gentner, in press.) We argue that single analogies that help novices to gain a preliminary grasp of difficult, complex concepts may later become serious impediments to fuller and more correct understandings. Specifically, although single analogies rarely if ever form the basis for a full understanding of a newly encountered concept, there is nevertheless a powerful tendency for learners to continue to limit their understanding to just those aspects of the new concept covered by mapping it to the old one. Analog...

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Medical school teachers must have an accurate idea of the doctor's clinical reasoning process (CRP) in order to provide students with learning experiences and evaluations that will ensure their acquisition of an effective and efficient CRP. It is difficult to derive this understanding from much that has been written on the subject. It is important to recognize that clinical problems are ill-structured and that the doctor's reasoning is built around a temporal unfolding of information. A model for the CRP is described along with a critique of other models that have been suggested. The results of research that examines components of the process must be seen in relation to the overall process.